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• Repository: https://gerrit.onap.org/r/#/admin/projects/dcaegen2/collectors/hv-ves
• Changes: https://gerrit.onap.org/r/#/q/project:dcaegen2/collectors/hv-ves

Purpose

The goal of the collector is to support high volume data. It uses plain TCP connections tunneled in SSL/TLS. Connections are stream-based (as opposed to request-based) and long running. Payload is binary-encoded (currently we are using Google Protocol Buffers). HV-VES uses direct connection to DMaaP's Kafka. All these decisions were made in order to support high-volume data with minimal latency.

For more details on the rationale, please read a high-level feature description.

Background

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Background

HV-VES collector has been proposed, based on a need to process high-volumes of data generated frequently by a large number of NFs. The driving use-case is the 5G RAN, where it is expected that up to 10k NF instances report the data, per DCAE platorm platform deployment. The network traffic generated in simulations - based on 4G BTS Real-Time PM data has shown, that GPB serialization is 2-3 times more effective, than JSON serialization utilized in VES collector.

Results have been published within ONAP presentation in Casablanca Release Developer Forum:  Google Protocol Buffers versus JSON - 5G RAN use-case - comparison

Implementation details

Technology stack

• Project Reactor is used as a backbone of the internal architecture.
• Netty is used by means of reactor-netty library.
• We are using Kotlin so we can write very concise code with great interoperability with existing Java libraries.
• Types defined in Λrrow library are also used when it improves readability or general cleanness of the code.

Rules

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The goal of the collector is to support high volume data. It uses plain TCP connections tunneled in SSL/TLS. Connections are stream-based (as opposed to request-based) and long running. Payload is binary-encoded (currently we are using Google Protocol Buffers). HV-VES uses direct connection to DMaaP's Kafka. All these decisions were made in order to support high-volume data with minimal latency.

For more details on the rationale, please read a high-level feature description.

Description

Compatibility aspects (VES-JSON)

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Analytics applications will have to be as well equipped with this new domain-specific PROTO file.
Currently, these additional, domain specific proto files could be simply added to respective repos of VES-HV collector.

Implementation details

Technology stack

• Project Reactor is used as a backbone of the internal architecture.
• Netty is used by means of reactor-netty library.
• We are using Kotlin so we can write very concise code with great interoperability with existing Java libraries.
• Types defined in Λrrow library are also used when it improves readability or general cleanness of the code.

Rules

• Do not block. Use non-blocking libraries. Do not use block* Reactor calls inside the core of the application.
• Pay attention to memory usage.
• Do not decode the payload - it can be of a considerable size. The goal is to direct the event into a proper Kafka topic. The routing logic should be based only on VES Common Header parameters.
• All application logic should be defined in hv-collector-core module and tested on a component level by tests defined in hv-collector-ct. The core module should have a clean interface (defined in boundary package: api and adapters).
• Use Either functional data type when designing fail-cases inside the main Flux. Using exceptions is a bit like using goto + it adds some performance penalty: collecting stack trace might be costly but we do not usually need it in such cases. RuntimeExceptions should be treated as application bugs and fixed.

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